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Trustworthy data science for improving healthcare efficiency: the case of the medical referral process
Mission of the project
Mission of the project
Trustworthy data science for improving healthcare efficiency: the case of the medical referral process
Characterizing specialty referral patterns to tackle organizational challenges
Characterizing specialty referral patterns to tackle organizational challenges
Perform a comparative analysis to characterize referral patterns between US and Portuguese health systems.
Accurate models for interpretable extreme classification, under imbalanced label distribution
Accurate models for interpretable extreme classification, under imbalanced label distribution
Produce a transparent predictor that will work under extreme classification and ill-posed, inverse problems.
Trustworthy recommender system
Trustworthy recommender system
Design a healthcare recommender system using graph neural networks and interpretable machine learning.
Dissemination, Management, and Ethics
Dissemination, Management, and Ethics
Interact with real world implementations and policy recommendations. that are tightly related with ethics and data curation guidelines.
Questions?
Questions?
Contact md2trust@gmail.com to get more information on the project
This project is funded by the Fundação para a Ciência e Tecnologia through the Carnegie Mellon Portugal Program under Grant CMU/TIC/0016/2021
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